docstr: Applies the transforms to the input image.
  
  Args:
      image:
          The input image to apply the transforms to.
  
  Returns:
      The transformed image.
docstr_tok: ["Applies","the","transforms","to","the","input","image",".","Args",":","image",":","The","input","image","to","apply","the","transforms","to",".","Returns",":","The","transformed","image","."]
code: def __call__(self, image: Union[Tensor, Image]) -> Tensor:
      """
      Applies the transforms to the input image.
  
      Args:
          image:
              The input image to apply the transforms to.
  
      Returns:
          The transformed image.
  
      """
      transformed: Tensor = self.transform(image)
      return transformed
  
file_path: lightly/lightly/transforms/byol_transform.py
imports: from typing import Dict, List, Optional, Tuple, Union
  import torchvision.transforms
  from PIL.Image import Image
  from torch import Tensor
  from lightly.transforms.gaussian_blur import GaussianBlur
  from lightly.transforms.multi_view_transform import MultiViewTransform
  from lightly.transforms.rotation import random_rotation_transform
  from lightly.transforms.solarize import RandomSolarization
  from lightly.transforms.utils import IMAGENET_NORMALIZE
label_desc: Use image node_id 2 for calling the BYOLView1Transform obj's underlying member method code with example usage: obj.__call__(image) and returns: transformed